7th Multidisciplinary Workshop on Advances in Preference Handling

Preference handling has become a flourishing topic. There are many interesting results, good examples for cross-fertilization between disciplines, and many new questions.

Preferences are a central concept of decision making. As preferences are fundamental for the analysis of human choice behavior, they are becoming of increasing importance for computational fields such as artificial intelligence, databases, and human-computer interaction. Preference models are needed in decision-support systems such as web-based recommender systems, in automated problem solvers such as configurators, and in autonomous systems such as Mars rovers. Nearly all areas of artificial intelligence deal with choice situations and can thus benefit from computational methods for handling preferences. Moreover, social choice methods are also of key importance in computational domains such as multi-agent systems.

This broadened scope of preferences leads to new types of preference models, new problems for applying preference structures, and new kinds of benefits. Preferences are studied in many areas of artificial intelligence such as knowledge representation, multi-agent systems, game theory, social choice, constraint satisfaction, decision making, decision-theoretic planning, and beyond. Preferences are inherently a multi-disciplinary topic, of interest to economists, computer scientists, operations researchers, mathematicians and more.

This workshop promotes this broadened scope of preference handling and continues a series of events on preference handling at AAAI-02, Dagstuhl in 2004, IJCAI-05, ECAI-06, VLDB-07, AAAI-08, ADT-09, ECAI-2010 and ECAI-2012. Since 2008, this series of workshops is organized by the multidisciplinary working group on Advances in Preference Handling, which is affiliated to the Association of European Operational Research Societies EURO.

The workshop provides a forum for presenting advances in preference handling and for exchanging experiences between researchers facing similar questions, but coming from different fields. The workshop builds on the large number of AI researchers working on preference-related issues, but also seeks to attract researchers from databases, multi-criteria decision making, economics, etc.

TOPICS OF INTEREST

The workshop on Advances in Preferences Handling addresses all computational aspects of preference handling. This includes methods for the elicitation, learning, modeling, representation, aggregation, and management of preferences and for reasoning about preferences. The workshop studies the usage of preferences in computational tasks from decision making, database querying, web search, personalized human-computer interaction, personalized recommender systems, e-commerce, multi-agent systems, game theory, social choice, combinatorial optimization, planning and robotics, automated problem solving, perception and natural language understanding and other computational tasks involving choices. The workshop seeks to improve the overall understanding of the benefits of preferences for those tasks. Another important goal is to provide cross-fertilization between different fields.

- Preference handling in artificial intelligence

Qualitative decision theory
Non-monotonic reasoning
Preferences in logic programming
Preferences for soft constraints in constraint satisfaction
Preferences for search and optimization
Preferences for AI planning
Preferences reasoning about action and causality
Preference logic

- Preference handling in database systems

Preference query languages for SQL and XML
Algebraic and cost-based optimization of preference queries
Top-k algorithms and cost models
Ranking relational data and rank-aware query processing
Skyline query evaluation
Preference management and repositories
Personalized search engines
Preference recommender systems

- Preference handling in multiagent systems

Game theory
(Combinatorial) auctions and exchanges
Social choice, voting, and other rating/ranking systems
Mechanism design and incentive compatibility

- Applications of preferences

Web search
Decision making
Combinatorial optimization and other problem solving tasks
Personalized human-computer interaction
Personalized recommendation systems
e-commerce and m-commerce

- Preference elicitation

Preference elicitation in multi-agent systems
Preference elicitation with incentive-compatibility
Learning of preferences
User preference mining
Revision of preferences

- Preference representation and modeling

Linear and non-linear utility representations
Multiple criteria/attributes
Qualitative decision theory
Graphical models
Logical representations
Soft constraints
Relations between qualitative and quantitative approaches

- Properties and semantics of preferences

Preference and choice
Preference composition, merging, and aggregation
Incomplete or inconsistent preferences
Intransitive indifference
Reasoning about preferences

* Important dates:
----------------------

Saturday, April, 20, 2013: Workshop paper submission deadline
Monday, May, 20, 2013: Notification on workshop paper submissions
Thursday, May, 30, 2013: Camera-ready copy due to organizers
August 3-4, 2013: M-PREF’13 Workshop

* Workshop chairs:
----------------------

Markus Endres, University of Augsburg, Germany
Souhila Kaci, Universite Montpellier 2, LIRMM, France
K. Brent Venable, Tulane University and IHMC, USA
Paolo Viappiani, CNRS & LIP6, Univ. Pierre et Marie Curie, France